Land-Use History and Contemporary Management Inform an Ecological Reference Model for Longleaf Pine Woodland Understory Plant Communities

Ecological restoration is frequently guided by reference conditions describing a successfully restored ecosystem; however, the causes and magnitude of ecosystem degradation vary, making simple knowledge of reference conditions insufficient for prioritizing and guiding restoration. Ecological reference models provide further guidance by quantifying reference conditions, as well as conditions at degraded states that deviate from reference conditions. Many reference models remain qualitative, however, limiting their utility. We quantified and evaluated a reference model for southeastern U.S. longleaf pine woodland understory plant communities. We used regression trees to classify 232 longleaf pine woodland sites at three locations along the Atlantic coastal plain based on relationships between understory plant community composition, soils (which broadly structure these communities), and factors associated with understory degradation, including fire frequency, agricultural history, and tree basal area. To understand the spatial generality of this model, we classified all sites together and for each of three study locations separately. Both the regional and location-specific models produced quantifiable degradation gradients–i.e., progressive deviation from conditions at 38 reference sites, based on understory species composition, diversity and total cover, litter depth, and other attributes. Regionally, fire suppression was the most important degrading factor, followed by agricultural history, but at individual locations, agricultural history or tree basal area was most important. At one location, the influence of a degrading factor depended on soil attributes. We suggest that our regional model can help prioritize longleaf pine woodland restoration across our study region; however, due to substantial landscape-to-landscape variation, local management decisions should take into account additional factors (e.g., soil attributes). Our study demonstrates the utility of quantifying degraded states and provides a series of hypotheses for future experimental restoration work. More broadly, our work provides a framework for developing and evaluating reference models that incorporate multiple, interactive anthropogenic drivers of ecosystem degradation.

生态修复常以描述成功修复生态系统的参照条件作为指导依据，但生态系统退化的成因与程度存在差异，仅依靠参照条件的相关知识，不足以对修复工作进行优先级排序与实施指导。生态参照模型则通过量化参照条件，以及偏离参照条件的退化状态下的生态系统状况，提供进一步的指导。然而，多数参照模型仍为定性模型，限制了其应用效能。本研究对美国东南部长叶松（longleaf pine）林地林下植物群落的参照模型进行了量化与评估。本研究依托林下植物群落组成、塑造此类群落的土壤因子，以及与林下退化相关的因素（包括火烧频率、农业开发历史与树木基面积）之间的关联，采用回归树（regression trees）方法，对大西洋沿海平原沿线3处研究地点的232处长叶松林地样地进行分类。为明确该模型的空间普适性，本研究同时对全部样地进行统一分类，并分别针对3处研究地点进行单独分类。区域模型与局地专属模型均生成了可量化的退化梯度——即基于林下物种组成、多样性与总盖度、枯落物厚度及其他属性，相较于38处参照样地的逐步偏离程度。从区域尺度来看，火烧抑制是最主要的退化驱动因子，其次为农业开发历史；但在单个研究地点中，农业开发历史或树木基面积则为首要退化因子。在其中一处研究地点，某一退化因子的影响程度取决于土壤属性特征。本研究认为，我们构建的区域模型可用于辅助本研究区域内长叶松林地修复工作的优先级排序；但由于不同景观间存在显著差异，局地管理决策应纳入额外考量因素（如土壤属性）。本研究证实了量化退化状态的应用价值，并为未来的修复实验研究提供了一系列假说。从更广泛的层面来看，本研究为开发与评估纳入多种交互性人为生态系统退化驱动因子的参照模型提供了一套研究框架。